Crop Photosynthesis Research Articles

Optimized irrigation practices with fertilizer utilization strategies to improve photo-fluorescence efficiency, vascular bundles and maize production in semi-arid regions

The mechanism of irrigation models combined with fertilizer utilization strategies under the biodegradable film mulching could greatly promote crop photosynthesis, vascular bundles structure; resource utilization and maize production are unclear in semi-arid areas. Unfortunately, this mechanism provides a scientific basis for improving irrigation and fertilizer utilization. A field study was carried out during 2021–2022 years. Seven treatments were established: two nitrogen levels: low-N (150 kg N ha−1) and high-N (300 kg N ha−1) combined with three different irrigation models: drip irrigation (DI), ridge irrigation (RI) and border irrigation (BI) under the biodegradable film mulching with (CK) treatment have no irrigation, fertilizer and mulching. Our results revealed that DIH treatment considerably increased soil water storage, enhanced photosynthesis rate (Pn) of maize by mainly to facilitate stomatal opening compared to the rest of all treatments. In addition, it also enhances the differentiation of the vascular bundle system and maintains its post silk function under better environmental conditions, greatly improving nitrogen storage in soil and plants, and enhancing maize productivity. DIH and RIH treatments significantly increased net photosynthesis rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), maximum quantum yield of PSII photochemistry (Fv/Fm), and effective quantum yield of PSII photochemistry (ΦPSII), photochemical quenching (qP), non-photochemical quenching (NPQ), and yield were observed, but evapotranspiration (ET) decreased at different growth stages. The results showed that DIH treatment was an effective tillage strategy, which increased biomass yield by 32.6 %, grain yield by 46.0 %, water use efficiency (WUE) by 46.2 %, and nitrogen use efficiency (NUE) by 86.4 % compared to other treatments. Given these results, thus we recommend the drip irrigation combined with a high-N level under a biodegradable film mulching increase photo-fluorescence efficiency, maize production and resource utilization efficiency in semi-arid regions.

Cross-species transcriptomics reveals differential regulation of essential photosynthesis genes in Hirschfeldia incana.

Photosynthesis is the only yield-related trait not yet substantially improved by plant breeding. Previously, we have established H. incana as the model plant for high photosynthetic light-use efficiency (LUE). Now we aim to unravel the genetic basis of this trait in H. incana, potentially contributing to the improvement of photosynthetic LUE in other species. Here, we compare its transcriptomic response to high light with that of Arabidopsis thaliana, Brassica rapa, and Brassica nigra, 3 fellow Brassicaceae members with lower photosynthetic LUE. We built a high-light, high-uniformity growing environment, in which the plants developed normally without signs of stress. We compared gene expression in contrasting light conditions across species, utilizing a panproteome to identify orthologous proteins. In-depth analysis of 3 key photosynthetic pathways showed a general trend of lower gene expression under high-light conditions for all 4 species. However, several photosynthesis-related genes in H. incana break this trend. We observed cases of constitutive higher expression (like antenna protein LHCB8), treatment-dependent differential expression (as for PSBE), and cumulative higher expression through simultaneous expression of multiple gene copies (like LHCA6). Thus, H. incana shows differential regulation of essential photosynthesis genes, with the light-harvesting complex as the first point of deviation. The effect of these expression differences on protein abundance and turnover, and ultimately the high photosynthetic LUE phenotype is relevant for further investigation. Furthermore, this transcriptomic resource of plants fully grown under, rather than briefly exposed to, a very high irradiance, will support the development of highly efficient photosynthesis in crops.

Enhancing Photosynthesis and Plant Productivity through Genetic Modification.

Enhancing crop photosynthesis through genetic engineering technologies offers numerous opportunities to increase plant productivity. Key approaches include optimizing light utilization, increasing cytochrome b6f complex levels, and improving carbon fixation. Modifications to Rubisco and the photosynthetic electron transport chain are central to these strategies. Introducing alternative photorespiratory pathways and enhancing carbonic anhydrase activity can further increase the internal CO2 concentration, thereby improving photosynthetic efficiency. The efficient translocation of photosynthetically produced sugars, which are managed by sucrose transporters, is also critical for plant growth. Additionally, incorporating genes from C4 plants, such as phosphoenolpyruvate carboxylase and NADP-malic enzymes, enhances the CO2 concentration around Rubisco, reducing photorespiration. Targeting microRNAs and transcription factors is vital for increasing photosynthesis and plant productivity, especially under stress conditions. This review highlights potential biological targets, the genetic modifications of which are aimed at improving photosynthesis and increasing plant productivity, thereby determining key areas for future research and development.

A Review of Drip Irrigation’s Effect on Water, Carbon Fluxes, and Crop Growth in Farmland

The substantial depletion of freshwater reserves in many pivotal agricultural regions, attributable to the dual pressures of global climate change and the excessive extraction of water resources, has sparked considerable apprehension regarding the sustainability of future food and water security. Drip irrigation, as an efficient and precise irrigation method, reduces water loss caused by deep percolation, soil evaporation, and runoff by controlling the irrigation dosage and frequency, thus improving the efficiency of water resource utilization. Studies have shown that compared with traditional irrigation methods, drip irrigation can significantly decrease water consumption, optimize the water–energy relationship by reducing soil evaporation, increase the leaf area index, and promote crop growth, thereby enhancing plant transpiration. Although more wet and dry soil cycles from drip irrigation may increase soil CO2 emissions, it also enhances crop photosynthesis and improves crop net ecosystem productivity (NEP) by creating more favorable soil moisture conditions, indicating greater carbon sequestration potential. The advantages of drip irrigation, such as a short irrigation cycle, moderate soil moisture, and obvious dry and wet interfaces, can improve a crop’s leaf area index and biomass accumulation, improve root dynamics, promote the distribution of photosynthetic products to the aboveground parts, and thus enhance crop yields. This study highlights the potential for the application of drip irrigation in arid regions where resource optimization is sought, providing strong technical support for the achievement of sustainable agricultural development. Future research needs to consider specific agricultural practices, soil types, and environmental conditions to further optimize the implementation and effectiveness of drip irrigation.

Nitrogen Reduction and Organic Fertiliser Application Benefits Growth, Yield, and Economic Return of Cotton

The application of excessive nitrogen fertiliser has been found to have a detrimental impact on the growth and development of cotton in Xinjiang, China. This has resulted in a reduction in cotton yield and economic benefit. The aim of this study was to investigate the potential for reducing the input of inorganic N fertiliser while maintaining the quality and yield formation of cotton. The objective of this study was to examine the growth, photosynthesis, and yield of cotton crops subjected to varying fertiliser treatments. The experiment was conducted in 2021–2022 with eight treatments in the experiment: no fertiliser (CK); conventional application of inorganic nitrogen fertiliser (T0); T1–T3, with 8%, 16%, and 24% reduction in inorganic nitrogen fertiliser application, respectively; and T4–T6, with organic fertilisers replacing the reduced inorganic nitrogen fertiliser application of T1–T3, respectively. In comparison to T0, T5 demonstrated the most notable agronomical performance and yield components across both years. This is attributable to the spatial distribution of cotton bolls, which was more conducive to the net photosynthetic rate and yield formation. This, in turn, led to an augmented photosynthetic capacity, enhanced biomass accumulation, and an elevated harvesting index. The results of the economic benefit analysis demonstrated that in comparison to the control treatment (T0), the net profit of all treatments except T3 increased. In conclusion, the economic benefit reached its maximum in the range of a 9.90–14.10% reduction in nitrogen and a 16.60–17.60% substitution of organic fertiliser.

Effects of microplastics and combined pollution of polystyrene and di-n-octyl phthalate on photosynthesis of cucumber (Cucumis sativus L.)

Photosynthesis provides carbon sources and energy for crop growth and development, and the widespread presence of microplastics and plastic plasticisers in agricultural soils affects crop photosynthesis, but the mechanism of the effect is not clear. This study aims to investigate the effects of different microplastics and plasticizers on cucumber photosynthesis. Using polyvinyl chloride (PVC), polyethylene (PE), polystyrene (PS), and di-n-octyl phthalate (DOP) as representative microplastics and plasticizers, we assessed their impact on cucumber photosynthesis. Our results reveal significant alterations in key parameters: intercellular CO2 concentration (Ci) and transpiration rate (Tr) increased across all treatments, whereas stomatal limit value (Ls) and water use efficiency (WUE) decreased. Notably, PS + DOP treatment led to a significant reduction in the maximum efficiency of photosystem II (Fv/Fm) and ATP accumulation. Furthermore, PE and PS + DOP treatments decreased lycopene and ɛ-carotene synthesis rates, as well as abscisic acid (ABA) accumulation. All treatments inhibited the conversion of β-carotene into strigolactone (SL) and decreased chlorophyll synthesis rates, with PS + DOP exhibiting the most severe impact. Regarding chlorophyll degradation pathways, PVC and PE treatments reduced chlorophyll decomposition rates, whereas DOP with PS promoted degradation. PE and PS treatments also impaired light energy capture, electron transport, and the structural stability of photosystems I and II, as well as photosynthetic capacity and NADPH and ATP synthesis rates. Our findings underscore the differential impacts of microplastics and plasticizers on cucumber photosynthesis, with PS + DOP having the most detrimental effect. These results shed light on the complex interactions between microplastics and plant physiology, highlighting the urgent need for mitigation strategies in agricultural practices to safeguard crop productivity and environmental sustainability.

Impacts of Drought on Photosynthesis in Major Food Crops and the Related Mechanisms of Plant Responses to Drought.

Drought stress is one of the most critical threats to crop productivity and global food security. This review addresses the multiple effects of drought on the process of photosynthesis in major food crops. Affecting both light-dependent and light-independent reactions, drought leads to severe damage to photosystems and blocks the electron transport chain. Plants face a CO2 shortage provoked by stomatal closure, which triggers photorespiration; not only does it reduce carbon fixation efficiency, but it also causes lower overall photosynthetic output. Drought-induced oxidative stress generates reactive oxygen species (ROS) that damage cellular structures, including chloroplasts, further impairing photosynthetic productivity. Plants have evolved a variety of adaptive strategies to alleviate these effects. Non-photochemical quenching (NPQ) mechanisms help dissipate excess light energy as heat, protecting the photosynthetic apparatus under drought conditions. Alternative electron pathways, such as cyclical electron transmission and chloroplast respiration, maintain energy balance and prevent over-reduction of the electron transport chain. Hormones, especially abscisic acid (ABA), ethylene, and cytokinin, modulate stomatal conductance, chlorophyll content, and osmotic adjustment, further increasing the tolerance to drought. Structural adjustments, such as leaf reordering and altered root architecture, also strengthen tolerance. Understanding these complex interactions and adaptive strategies is essential for developing drought-resistant crop varieties and ensuring agricultural sustainability.

Photosynthetic productivity of soybean (Glycine max L.) crops under various fertilization options and pre-sowing seed treatment

The objective of the research is to determine the impact of basic fertilization options, foliar feeding with organo-mineral fertilizer during critical periods of soy plant development, pre-sowing seed treatment with mycorrhizal biofertilizer, and mycorrhizal inoculant in combination with a fungicide on the dynamics of dry matter accumulation by the plants and the net productivity of photosynthesis in the soy crop. Methods. Field (for studying the interaction of the research object with biotic and abiotic factors); morphophysiological (for biological monitoring of productivity elements development during organogenesis stages); statistical (statistical analysis of research results). Results. The article presents research findings on the accumulation of dry matter by soy plants and the net productivity of photosynthesis in the crop across different growth and development stages. Equations have been calculated to establish the relationship between soy seed yield and the indicators of dry mass accumulation by the plants during the pod-filling phase. Conclusions. In modern agricultural practices aimed at achieving maximum seed yield, cultivation technology should include agronomic measures directed towards meeting the biological needs of the plant throughout the vegetation period and reducing the influence of adverse external factors. The highest levels of dry matter accumulation by plants in the study — 26.8–29.2 g/plant, were noted during the pod filling phase in variants with the application of N15P45K60+N30 fertilization, sowing seeds treated with mycorrhizal biopreparation and fungicide, and foliar feeding with organo-mineral fertilizers during the budding and flowering phases. The maximum indicators of net photosynthetic productivity of the crop in the study (8.52–11.29 g/m2×day compared to 5.46 g/m2×day in the absolute control) were observed during the interphase period of flowering and pod filling in variants with N45P45K60 fertilization. For the optimal seed yield of soybean variety Muza observed in the study, the optimal conditions were provided by a cultivation technology involving the application of N15P45K60+N30 fertilizers, pre-sowing seed treatment with mycorrhizal inoculant in combination with fungicide, as well as foliar feeding with organo-mineral fertilizers during the branching or budding phases, when the plants are forming flowers, pods, and seeds within the pods. Through the combination of these agronomic measures, plants accumulate dry matter during the pod filling phase at 25.9–27.4 g/plant, ensuring the net photosynthetic productivity of the crop during this developmental period at 5.60–6.10 g/m2×day, compared to 20.8 g/plant and 5.46 g/m2×day observed in the absolute control, respectively.

Plant Biostimulants Enhance Tomato Resilience to Salinity Stress: Insights from Two Greek Landraces

Salinity, one of the major abiotic stresses in plants, significantly hampers germination, photosynthesis, biomass production, nutrient balance, and yield of staple crops. To mitigate the impact of such stress without compromising yield and quality, sustainable agronomic practices are required. Among these practices, seaweed extracts (SWEs) and microbial biostimulants (PGRBs) have emerged as important categories of plant biostimulants (PBs). This research aimed at elucidating the effects on growth, yield, quality, and nutrient status of two Greek tomato landraces (‘Tomataki’ and ‘Thessaloniki’) following treatments with the Ascophyllum nodosum seaweed extract ‘Algastar’ and the PGPB ‘Nitrostim’ formulation. Plants were subjected to bi-weekly applications of biostimulants and supplied with two nutrient solutions: 0.5 mM (control) and 30 mM NaCl. The results revealed that the different mode(s) of action of the two PBs impacted the tolerance of the different landraces, since ‘Tomataki’ was benefited only from the SWE application while ‘Thessaloniki’ showed significant increase in fruit numbers and average fruit weight with the application of both PBs at 0.5 and 30 mM NaCl in the root zone. In conclusion, the stress induced by salinity can be mitigated by increasing tomato tolerance through the application of PBs, a sustainable tool for productivity enhancement, which aligns well with the strategy of the European Green Deal.

Effects of Organic Fertilizer on Photosynthesis, Yield, and Quality of Pakchoi under Different Irrigation Conditions.

Water scarcity and the overuse of chemical fertilizers present significant challenges to modern agriculture, critically affecting crop photosynthesis, yield, quality, and productivity sustainability. This research assesses the impact of organic fertilizer on the photosynthetic attributes, yield, and quality of pakchoi under varying irrigation water conditions, including fresh water and brackish water. Findings reveal that the modified rectangular hyperbolic model most accurately captures the photosynthetic reaction to organic fertilization, outperforming other evaluated models. The maximum net photosynthesis rate (Pnmax), yield, soluble sugar (SS), and soluble protein content (SP) all exhibited a downward-opening quadratic parabolic trend with increasing amounts of organic fertilizer application. Specifically, under fresh-water irrigation, the optimal Pnmax, yield, SS, and SP were obtained at organic fertilizer rates of 65.77, 74.63, 45.33, and 40.79 kg/ha, respectively, achieving peak values of 20.71 µmol/(m2·s), 50,832 kg/ha, 35.63 g/kg, and 6.25 g/kg. This investigation provides a foundational basis for further research into the intricate relationship between water salinity stress and nutrient management, with the goal of crafting more sophisticated and sustainable farming methodologies. The insights gained could significantly influence organic fertilizer practices, promoting not only higher yields but also superior quality in agricultural outputs.

Response of rhizosphere microbial community structure and production performance of corn and soybean to belt planting mode

Soybean and corn strip cropping takes full advantage of the root characteristics and plant height differences between soybean and corn, which can improve crop photosynthesis and nutrient uptake as well as capitalize on the marginal effect of corn. However, there is not enough in-depth research on the effects of soybean and corn strip cropping modes on inter-root microbial communities and crop yield traits and their correlations, and the functional genes of inter-root microbes. In this study, the structural composition and functional genes of soil inter-root microbial communities under different strip cropping patterns of soybean and maize, Mode 1, Mode 2, and Mode 3, were studied using macro-genome high-throughput sequencing, and the yield traits of soybean and maize were determined and the correlation was understood, taking Zhonglian Soybean 1505 and Tiyu 108 maize as test materials at the experimental base of the Research Institute of Agricultural and Livestock Sciences, Xing'anmeng, Inner Mongolia. correlation between the two. The following results were found. Redundancy analysis found that rhizosphere microorganisms are mainly bacteria, followed by viruses, followed by archaea, and fungi are the least. Relatively speaking, viruses and bacteria are more susceptible to the influence of planting patterns than fungi. Alpha diversity analysis shows that the diversity index changes significantly during the peak flowering period. There is no difference between the other two stages. The diversity of maize rhizosphere microorganisms under Mode 1 or Mode 2 modes is higher than that under Mode 3 modes, while the diversity of soybean rhizosphere microorganisms under Mode 3 modes is higher than the other two modes. Profiling analysis found that different growth periods and planting patterns lead to varying degrees of changes in community structure. The dominant bacterial phyla include Pseudomonas, Actinobacteria, Bacteroidetes, and Streptococcus. The dominant genera of bacteria are rhizobia, pseudomonas, erythrobacteria, and pseudomonas. The relative abundance of slow root rhizobia in the three growth stages of maize rhizosphere is relatively low. The results of yield traits showed that corn yield under Mode 1 and Mode 2 planting was significantly higher than that under pattern III; soybean yield under pattern III planting was significantly higher than that under the other two patterns, indicating that pattern I or II planting is suitable for corn production, while Mode 3 planting mode is more suitable for soybean production. Correlation analysis showed that S_Massilis_putida was significantly and positively correlated with maize yield, and S_lysobacter_capsici was highly significantly and significantly positively correlated with the number of soybean plants per square meter, and the number of plants in 2 square meters. This study contributes to our further understanding of the classification of inter-root microorganisms and their functional relationships in maize and soybean under different conditions.

An Economical Sensor-Based Automated Plant Watering System for Smart Irrigation

Lack of water results in a reduction in photosynthesis in plants and crops. Plants are significantly affected when the soil water level is depleted thereby resulting in low production in the agricultural sector which can lead to a reduction in food supply. This problem makes water supply and management highly necessary for plants to grow effectively. Over the past century, the rate at which water usage has increased globally has increased at a rate higher than that of population growth. Particularly in dry regions, an increasing number of regions are now using more water than they can sustainably provide. The traditional watering techniques, such as sprinklers and flood mode, are ineffective and those not supply the ideal needs of plants because some plants do not need excess water to grow. This also results in water wasting. These ineffective irrigation systems often provide habitat for organisms that carry illnesses. Research has established that excessive water spillage and stagnant water can be habitat for mosquitoes which can also be dangerous to human health. Therefore, watering plants must be done intelligently, by developing an intelligent system that can regulate the content of water needed to water a plant in accordance with their needs and the moisture content of the soil. This will also reduce the spillage of water. In this study, an automated plant watering system that monitors the soil's moisture level to determine when watering plants is necessary was developed using hardware components such as Arduino UNO (Microcontroller), soil moisture sensor, pump, relays, wires, sprinkler and software instructions to drive the hardware components. An economical watering system was designed. The system was tested and can be effectively used in small gardens and big crop fields.

Effects of Cu2O nanoparticles on the kinetic characteristics of rapid chlorophyll fluorescence induction and related genes in wheat seedlings.

Metal nanoparticles could be accumulated in soils, which threatens the ecological stability of crops. Investigating the effects of cuprous oxide nanoparticles (Cu2O-NPs) on photosystem Ⅱ (PSⅡ) of wheat seedling leaves holds considerable importance in comprehending the implications of Cu2O-NPs on crop photosynthesis. Following the hydroponic method, we investigated the effects of 0, 10, 50, 100, and 200 mg·L-1 Cu2O-NPs on chlorophyll fluorescence induction kinetics and photosynthetic-related genes in wheat seedlings of "Zhoumai 18". The results showed that, with the increases of Cu2O-NPs concentrations, chlorophyll contents in wheat leaves decreased, and the standardization of the OJIP curve showed a clearly K-phase (ΔK＞0). Cu2O-NPs stress increased the parameters of active PSⅡ reaction centers, including the absorption flux per active RC (ABS/RC), the trapping flux per active RC (TRo/RC), the electron transport flux per active RC (ETo/RC), and the dissipation flux per active RC (DIo/RC). Cu2O-NPs stress decreased the parameters of PSⅡ energy distribution ratio including the maximum quantum yield of PSⅡ (φPo), the quantum yield of electron transport from QA (φEo), and the probability that a trapped exciton moved an electron further than QA (Ψo), while increased the quantum ratio for heat dissipation (φDo). Moreover, there was a decrease in photosynthetic quantum yield Y(Ⅱ), photochemical quenching coefficient (qP), net photosynthetic rate (Pn), stomatal conductance (gs), intercellular CO2 concentration (Ci), and transpiration rate (Tr) of leaves with the increases of Cu2O-NPs concentration. Under Cu2O-NPs stress, the expression levels of genes which included PSⅡ genes (PsbD, PsbP, Lhcb1), Rubisco large subunit genes (RbcL), cytochrome b6/f complex genes (PetD, Rieske), and ATP synthase genes (AtpA, AtpB, AtpE, AtpI) were downregulated. These results indicated that Cu2O-NPs stress altered the activity and structure of PSⅡ in wheat seedlings, affected the activity of PSⅡ reaction centers, performance parameters of PSⅡ donor and acceptor sides. PSⅡ related genes were downregulated and exhibited significant concentration effects.

Low CO2 concentration, a key environmental factor for developing plateau adapted rapeseed

BackgroundPhotosynthesis is a fundamental process that underlies the formation of crop yield, wherein light serves as the driving force and carbon dioxide (CO2) as the raw material. These two factors have a direct influence on the progress and efficiency of photosynthesis in crops. Rapeseed is one of the four major oilseed crops worldwide. Plateau rapeseed has now become a research hotspot. However, the lack of high-yielding rapeseed germplasm resources on the plateau and the highly efficient strategy for screening them severely affect the development of rapeseed industry in plateau.ResultsIn the rapeseed experimental fields located on the plateau (Lhasa, Tibet), we measured abundant sunlight, characterized by an average daily photosynthetically active radiation (PAR) of 1413 μmol m−2 s−1. In addition, the atmospheric CO2 concentrations range from 300 to 400 ppm, which is only two-thirds of that in the plain (Chengdu, Sichuan). We found that under different measurement conditions of light intensity and CO2 concentration, different rapeseed genotypes showed significant differences in leaf photosynthetic efficiency during the seedling stage. Moreover, the rapeseed materials with high photosynthetic efficiency under low CO2 concentrations rather than high light intensity, exhibited significant advantages in biomass, yield, and oil content when cultivated on the plateau, indicating that the CO2 is the key environmental factor which limited rapeseed production in plateau. Based on photosynthetic efficiency screening under low CO2 concentrations, six rapeseed varieties SC3, SC10, SC25, SC27, SC29 and SC37, shown significantly higher yields in plateau environment compared to local control variety were obtained. In addition, the adaptability of rapeseed to plateau was found to be related to the activities of key Calvin cycle enzymes and the accumulation of photosynthetic products.ConclusionsThis study established a screening strategy for plateau high-yielding rapeseed materials, obtained six varieties which were suitable for plateau cultivation, explored the mechanism of rapeseed response to the plateau environment, and thus provides a feasible strategy for plateau-adapted rapeseed breeding.

Modeling of Cotton Yield Estimation Based on Canopy Sun-Induced Chlorophyll Fluorescence

Cotton yield estimation is of great practical significance to producers, allowing them to make rational management decisions. At present, crop yield estimation methods mainly comprise traditional agricultural yield estimation methods, which have many shortcomings. As an ideal “probe” for detecting crop photosynthesis, sun-induced chlorophyll fluorescence (SIF) can directly reflect the dynamics of actual crop photosynthesis and has the potential to predict crop yield, in order to realize cotton yield estimation based on canopy SIF. In this study, we set up field trials with different nitrogen fertilizer gradients. The changes of canopy SIF and the physiological parameters of cotton in different growth periods were analyzed. To investigate the effects of LAI and AGB on canopy SIF estimation of cotton yield, four algorithms, Ada Boost (Adaptive Boosting), Bagging (Bootstrap Aggregating), RF (Random Forest), and BPNN (Backpropagation Neural Network), were used to construct cotton yield estimation models based on the SIF and SIFy (the normalization of SIF by incident photosynthetically active radiation) for different time and growth periods. The results include the following: (1) The effects of the leaf area index (LAI) and aboveground biomass (AGB) on cotton canopy SIF and cotton yield were similar. The correlation coefficients of LAI and AGB with cotton yield and SIF were significantly positively correlated with each other starting from the budding period, reaching the maximum at the flowering and boll period, and decreasing at the boll period; (2) In different monitoring time periods, the R2 of the cotton yield estimation model established based on SIF and SIFy showed a gradual increase from 10:00 to 14:00 and a gradual decrease from 15:00 to 19:00, while the optimal observation time was from 14:00 to 15:00. The R2 increased with the progression of growth from the budding period to the flowering and boll period and decreased at the boll period, while the optimum growth period was the flowering and boll period; (3) Compared to SIF, SIFy has a superior estimation of yield. The best yield estimation model based on the RF algorithm (R2 = 0.9612, RMSE = 66.27 kg·ha−1, RPD = 4.264) was found in the canopy SIFy of the flowering and boll period at 14:00–15:00, followed by the model utilizing the Bagging algorithm (R2 = 0.8898) and Ada Boost algorithm (R2 = 0.8796). In summary, SIFy eliminates the effect of PAR (photosynthetically active radiation) on SIF and can further improve the estimation of SIF production. This study provides empirical support for SIF estimation of cotton yield and methodological and modeling support for the accurate estimation of cotton yield.

TRACES OF GLYPHOSATE IN CORN (Zea mays L.) AND AVOCADO (Persea americana Mill.) WEEDS SUPPORTED BY VANT AND RAMAN SPECTROSCOPY

Since the 1990s, radiometric and biophotonic sensor applications have provided reliable alternatives and rapid non-invasive diagnostics for the detection and delimitation of pests and diseases, as well as pesticide traces. Active sensors have been shown to be more accurate in detecting the heterogeneity of environmental factors based on thermal and infrared characteristics, chlorophyll fluorescence, and plant reflectance. Unmanned Aerial Vehicles (UAVs) equipped with infrared cameras locate and delimit weed abundance and diversity using Normalized Difference Vegetation Index (NDVI) algorithms, which highlight heterogeneous chlorophyll activity and herbicide-limited photosynthesis in crops. The resulting map serves as the foundation for collecting plant samples. In this study, the technology of these sensors was applied to determine glyphosate traces using Raman spectroscopy, which allowed a quick, low-cost, simple, and practical diagnosis with immediate results. These are essential characteristics for surveillance and monitoring activities, as well as the basis for a geo-referenced inventory of pesticides in production units. Of the 44 weed samples collected, eight were positive for glyphosate traces: two in corn and six in avocado. Weeds are identified as positive to glyphosate traces in Raman spectroscopy in the carotenoid and phenylpropanoid reduction ranges (1186 and 1213 cm-1) as a result of a decrease in the immune response. The vibrations presented by the amines in glyphosate and the C-OH of the carboxyl group are detected in the range of 1565 and 1567 cm-1.

Estimating the SPAD of Litchi in the Growth Period and Autumn Shoot Period Based on UAV Multi-Spectrum

The relative content of chlorophyll, assessed through the soil and plant analyzer development (SPAD), serves as a reliable indicator reflecting crop photosynthesis and the nutritional status during crop growth and development. In this study, we employed machine learning methods utilizing unmanned aerial vehicle (UAV) multi-spectrum remote sensing to predict the SPAD value of litchi fruit. Input features consisted of various vegetation indices and texture features during distinct growth periods, and to streamline the feature set, the full subset regression algorithm was applied for dimensionality reduction. Our findings revealed the superiority of stacking models over individual models. During the litchi fruit development period, the stacking model, incorporating vegetation indices and texture features, demonstrated a validation set coefficient of determination (R2) of 0.94, a root mean square error (RMSE) of 2.4, and a relative percent deviation (RPD) of 3.0. Similarly, in the combined litchi growing period and autumn shoot period, the optimal model for estimating litchi SPAD was the stacking model based on vegetation indices and texture features, yielding a validation set R2, RMSE, and RPD of 0.84, 3.9, and 1.9, respectively. This study furnishes data support for the precise estimation of litchi SPAD across different periods through varied combinations of independent variables.

Multiple invasive species affect germination, growth, and photosynthesis of native weeds and crops in experiments

Alien plant species regularly and simultaneously invade agricultural landscapes and ecosystems; however, the effects of co-invasion on crop production and native biodiversity have rarely been studied. Secondary metabolites produced by alien plants may be allelopathic; if they enter the soil, they may be transported by agricultural activities, negatively affecting crop yield and biodiversity. It is unknown whether substances from different alien species in combination have a greater impact on crops and wild plants than if they are from only one of the alien species. In this study, we used a set of common garden experiments to test the hypothesis that mixed extracts from two common invasive species have synergistic effects on crops and weeds (defined as all non-crop plants) in European agricultural fields compared to single-species extracts. We found that both the combined and individual extracts had detrimental effects on the seed germination, seedling growth, biomass, and photosynthetic performance of both crops and weeds. We found that the negative effect of mixed extracts was not additive and that crop plants were more strongly affected by invasive species extracts than the weeds. Our results are important for managing invasive species in unique ecosystems on agricultural land and preventing economic losses in yield production.

Exploring the responses of crop photosynthesis to CO2 elevation at the molecular, physiological, and morphological levels toward increasing crop production

Exploring the impact of elevated CO2 on photosynthesis is vital for understanding plant responses to climate change. In C3 plants, elevated CO2 concentrations generally enhance CO2 assimilation by increasing chloroplast CO2 concentration. However, the underlying mechanisms are complex since photosynthesis involves multiple physiological processes operating at different time scales and varying among plant species. In this review, we focused on the responses of key photosynthetic processes in crop, including CO2 diffusion conductances such as stomatal conductance (gs), mesophyll conductance (gm), photochemical reactions, the Calvin-Benson cycle, and related metabolic pathways. Short-term exposure to elevated CO2 often decreases gs and gm while increasing the electron transport rate. However, long-term exposure to elevated CO2 can decrease photosynthetic capacity due to coordinated downregulation of multiple processes, particularly when the sink‒source ratio declines. To enhance plant productivity under elevated CO2, it is crucial to maintain or enhance sink activity and understand the CO2 response mechanisms at the molecular, physiological, and morphological levels. This review provides an update on the short- and long-term responses of gs, gm, electron transport system, and carbon assimilation metabolism to elevated CO2. Furthermore, it offers a perspective on improving crop production in the future with elevated CO2 levels.

A cooperative regulation method for greenhouse soil moisture and light using Gaussian curvature and machine learning algorithms

Soil moisture (SM) exerts a significant impact on crop growth, interacting with environmental factors such as temperature, photosynthetic photon flux density (PPFD), and CO2, ultimately affecting crop photosynthesis (Pn). This study employs a nested experimental design to investigate the photosynthetic activity of cucumber seedlings under diverse environmental conditions and establishes a support vector regression (SVR) model for Pn prediction. The SVR model takes temperature, PPFD, SM, and CO2 concentration as inputs and demonstrates a high level of accuracy (The model’s coefficient of determination = 0.9830, root mean square error = 0.9138). Subsequently, through a generalized additive model, the study unveils the significant impact of interactions between SM and PPFD on Pn. Accordingly, this research constructs a Pn response surface based on these two factors and identifies the maximum point of Gaussian curvature on this surface. Polynomial regression is applied to these points, yielding a comprehensive regulation strategy for SM and PPFD. In comparison to traditional methods based on maximizing Pn, this innovative approach reduces Pn by 12.9 % while significantly conserving light (35.59 %) and water (32.80 %) consumption. Although no significant changes are observed in crop physiological traits (plant height, stem diameter, dry weight, fresh weight), substantial variations are noted in irrigation volume and PPFD consumption. Thus, the regulation strategy proposed in this study embodies efficiency and energy conservation in greenhouse crop cultivation.